Spatial Variability of Heat-Related Mortality in Barcelona from 1992-2015: A Case Crossover Study Design

Numerous studies have demonstrated the relationship between summer temperatures and increased heat-related deaths. Epidemiological analyses of the health effects of climate exposures usually rely on observations from the nearest weather station to assess exposure-response associations for geographically diverse populations. Urban climate models provide high-resolution spatial data that may potentially improve exposure estimates, but to date, they have not been extensively applied in epidemiological research. We investigated temperature-mortality relationships in the city of Barcelona, and whether estimates vary among districts. We considered georeferenced individual (natural) mortality data during the summer months (June&ndash
September) for the period 1992&ndash
2015. We extracted daily summer mean temperatures from a 100-m resolution simulation of the urban climate model (UrbClim). Summer hot days (above percentile 70) and reference (below percentile 30) temperatures were compared by using a conditional logistic regression model in a case crossover study design applied to all districts of Barcelona. Relative Risks (RR), and 95% Confidence Intervals (CI), of all-cause (natural) mortality and summer temperature were calculated for several population subgroups (age, sex and education level by districts). Hot days were associated with an increased risk of death (RR = 1.13
95% CI = 1.10&ndash
1.16) and were significant in all population subgroups compared to the non-hot days. The risk ratio was higher among women (RR = 1.16
95% CI= 1.12&ndash
1.21) and the elderly (RR = 1.18
95% CI = 1.13&ndash
1.22). Individuals with primary education had similar risk (RR = 1.13
95% CI = 1.08&ndash
1.18) than those without education (RR = 1.10
95% CI= 1.05&ndash
1.15). Moreover, 6 out of 10 districts showed statistically significant associations, varying the risk ratio between 1.12 (95% CI = 1.03&ndash
1.21) in Sants-Montju&iuml
c and 1.25 (95% CI = 1.14&ndash
1.38) in Sant Andreu. Findings identified vulnerable districts and suggested new insights to public health policy makers on how to develop district-specific strategies to reduce risks.